Analytics is fundamentally reshaping B2B interactions, unlocking new possibilities
Technology is fast evolving and so is the realm of Business-to-Business (B2B) interactions. Businesses aim to drive informed decisions while optimising operations by implementing analytics and AI solutions that align with their business goals and complement existing processes.
Analytics is a crucial growth driver for B2B businesses. It helps companies design and refine their products and services by analysing customer feedback, market trends, and competitor offerings, leading to efficient product development strategies aligned with customer requirements.
To drive business growth in the B2B business model, capturing the five-staged cyclical process is crucial – “segmentation”, “maintain and grow”, “offer the right price”, “bundled pricing,” and “lead management.”
Segmentation
To tailor marketing messages and sales strategies, the classification of existing customers into distinct groups acts as the first step to lay out business intent to drive a dedicated strategy for each cohort. While a few groups may belong to the premium segment and businesses need to upsell them, other groups of customers can be a focus of retention or win-back campaigns. These intents range from “Protect”, “Invest”, “Evolve”, “Develop”, “Scale”, and “Sustain”. Features such as the industry, company size, location, recurring revenue, wallet share, complexity of products purchased, tenure, and value at risk give a fair idea of customer profiles. This information also helps lay the groundwork to drive the next stage of the five-staged cycle.
Maintain and grow
Maintaining existing customer relations is essential in a B2B set-up. With the aim to safeguard and preserve these relations, two major target audiences need to be approached with the intent of protecting: the premium clients with a long-standing relationship and the clients who are at risk of churning.
This can be achieved by analysing prevailing churn trends across business units, products, and sectors. An effective retention strategy can be designed using advanced analytics, along with the appropriate expertise, to test and validate churn models across these segments.
The focus should be on identifying opportunities for upselling and cross-selling, to generate more revenue from existing clients. Businesses now use AI to analyse user interactions and target specific products to customers, based on their historical purchase patterns and monitor other customers with similar characteristics.
Businesses look to drive effectiveness instead of blanket marketing to increase sales opportunities and conversions, in addition to diversifying customer portfolios for enhanced business opportunities.
Offer the right price
To accelerate growth, the most crucial stage turns out to be offering the right price to customers. Right pricing not only achieves improved deal conversion rates but also ensures better profits for the overall business.
Whether it is a renewal, retention, upselling, or identifying prospective leads, pricing and retention teams require comprehensive and transparent pricing frameworks to address multiple KPIs to arrive at optimal pricing.
Bespoke pricing frameworks are designed to tackle growth for existing customers and new leads. KPIs such as churn propensity, price elasticity, next-best recommendations, pay ability, deal size, discounts, and contract duration, can provide guidance to achieve the optimal pricing for pricing teams to make evidence-based decisions. Understanding the characteristics of new customers, such as wallet share, sector, potential revenue targets, and their interests towards product purchases, can assist sales teams in driving meaningful conversations with new prospects.
The foundational element of the pricing framework is to assist sales executives and pricing teams to drive higher customer conversions and growth.
Bundled pricing
Dynamic pricing strategies such as discounts, promotions, and bundle offer, can be used to drive sales and boost revenue during specific periods or target specific customer segments. Bundle pricing, an effective strategy commonly used in B2B businesses, aims to attract customers to buy more items by emphasizing the cost savings achieved through the bundled offer.
ML algorithms, such as item-based collaborative filtering or Bayesian methods, can help learn existing purchase behaviour to recommend product combinations/bundles that are likely to be sold. This enables them to treat optimal deal packages to propose to prospective clients, cross-sell products, or upsell customers to higher-tier options.
Lead management
Besides the opportunities from existing customers, businesses should acquire new customers through growth perspectives. Laying an effective lead management strategy includes scoring leads, qualifying future customers, bringing personalisation in terms of product bundling and discounts, prioritising customers based on potential sales, and finally converting them.
Lead management focuses on the historical purchases and behavioural patterns of potential leads and forecasts that are crucial to estimate revenue, profit, and rate of interest from customers. AI and ML can be a formidable approach to devise an effective strategy to manage leads.
A prospective client could be mapped to an already existing customer base on the basis of factors such as company size, potential revenue generation, and product holding, to study their potential to help businesses design bespoke deals for them. Along with determining similar customers, predictive analytics can be used to get churn propensity and product preferences, and customer affinities, enabling sales managers to put forward the company’s best product ranges to prospects.
Analytics is fundamentally reshaping B2B interactions, unlocking new possibilities for personalised experiences, improved efficiency, and data-driven decision-making. As businesses harness the power of analytics, they can elevate their B2B relationships, streamline operations, and position themselves for success in a technology-driven marketplace. The journey has just begun, and the future of B2B holds significant potential fueled by the capabilities of analytics.
(This article is authored by Varun Rastogi, Partner, Consulting, Deloitte India and Nupur Aggarwal, Associate Director, Consulting, Deloitte India)
